ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DARTMOUTH, MA · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/dartmouth/2022-annual-report
Yearly Traffic Safety Analysis
582 CRASHES IN
DARTMOUTH, MA
2022
In 2022, Dartmouth recorded 582 total traffic crashes, representing a 3.6% decrease from the 604 crashes reported in 2021. While the total number of crashes saw a slight decline, the most significant change was a 50% reduction in traffic fatalities, which fell from 4 in 2021 to 2 in 2022.
582
▼ -3.6%was 604
Total Crash Events
2
▼ -50.0%was 4
Persons Killed
231
Persons Injured
8
▼ -27.3%was 11
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 15 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic crashes in Dartmouth showed a modest decrease from 2021 to 2022. Total crashes fell by 3.6%, from 604 to 582. Notably, the number of fatalities was halved, decreasing from 4 to 2, while the total number of injuries remained unchanged at 231 for both years.
8
Hit-and-Run Crashes — 2022
▼ -27.3% vs prior (11)
The number of hit-and-run incidents decreased from 2021 to 2022. There were 8 hit-and-run crashes reported in 2022, down from 11 the previous year. Correspondingly, the hit-and-run rate, which represents the percentage of total crashes that were hit-and-runs, declined from 1.8% in 2021 to 1.4% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
5
Pedestrians Injured
2
Cyclists Injured
224
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. In 2022, the peak day for crashes was Tuesday with 106 incidents, a change from Friday which was the peak day in 2021 with 98 incidents. The peak hour for crashes also shifted later in the day, moving from 3 p.m. in 2021 (60 crashes) to 5 p.m. in 2022 (51 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed a mixed profile year-over-year, with the fatal crash rate decreasing from 0.7% of all crashes in 2021 to 0.3% in 2022. The proportion of serious injury crashes also declined from 3.0% to 2.1%. However, the share of minor injury crashes increased from 16.6% in 2021 to 21.8% in 2022, while the share of crashes with no injuries decreased from 69.2% to 66.7%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors cited in crashes remained consistent between 2021 and 2022, with 'Inattention' being the most common factor in both years. The count of crashes attributed to inattention increased by 4.8%, from 105 in 2021 to 110 in 2022. Conversely, crashes involving 'Failed to yield right of way' decreased in count from 62 to 57. The top three primary factors—Inattention, No improper driving, and Failed to yield right of way—held the same rank in both years.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both years predominantly occurred in clear weather on dry roads during daylight hours. In 2022, the proportion of crashes happening in daylight decreased to 63.6% from 68.4% in 2021, while crashes in 'Dark - lighted roadway' conditions increased from a 17.7% share to a 22.5% share. The most notable shift in conditions was related to weather, as crashes occurring in snow dropped from 25 incidents in 2021 to 5 in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes were highly consistent year-over-year, with Toyota, Honda, and Ford remaining the top three most frequently involved makes in both 2021 and 2022. When examining the age of persons involved in crashes, the 16-20 age group saw its representation increase from 13.1% of all persons in 2021 to 14.8% in 2022. Conversely, the 26-34 age group's share of involved persons decreased from 16.6% to 15.5% over the same period.
Top Vehicle Makes (1,009 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
78 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,216 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained largely stable, with the 30 mph and 40 mph zones each accounting for a similar number of incidents in both 2021 and 2022. There was a decrease in crashes within the 65 mph zone, falling from 81 in 2021 to 66 in 2022. Fatalities in 2021 were spread across four different speed zones, whereas both fatalities recorded in 2022 occurred in the 65 mph zone.
Fatal crashes by zone: 65 mph: 2 of 66 (3.03%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Arcgis_yearly Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: DARTMOUTH, MA
- Total crash records analyzed: 582
- Total persons involved: 1,298
- Total vehicles involved: 1,009
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "DARTMOUTH, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dartmouth/2022-annual-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved